Proposals for Further Research - Revealing the State of Software-as-a-Service Pricing

5 Discussion 43

5.3 Proposals for Further Research

This dissertation also has practical implications for industry professionals, including consultants and managers in software companies responsible for pricing. The proposed typology of SaaS pricing practices may help companies to profile themselves in the space of SaaS solutions. This profiling supplements with the proposed classifications of aspects, affecting factors, structures, and frameworks enables companies to improve their pricing processes and practices.

5.3

Proposals for Further Research

The current dissertation revealed a clear picture of the current state of SaaS pricing. As comprehensive and complete research in its essence, the dissertation unlocks and highlights many opportunities for further research in the field of pricing in the context of SaaS and software solutions in general. An extensive list of further studies required to close the theory-practice gap and bridge different research perspectives on SaaS pricing was proposed in Publication II. Below, three particularly promising research opportunities that would contribute to understanding SaaS pricing and offer SaaS pricing decision-support solutions are discussed in detail. All three form a logical continuation of the studies included in the current dissertation.

• The findings of the industry survey presented in Publication III provide a valuable overview of SaaS pricing practices. However, the analysis was limited to a descriptive analysis and matching them with current pricing theories.

Furthermore, the scope of the study did not cover the entire population of SaaS companies. Additionally, publicly available data can be supplemented with data from more extensive surveys. A larger-scale study based on a more considerable amount of data and more sophisticated methods of analysis would allow a comparison of SaaS pricing practices in different contexts and reveal a more comprehensive typology of SaaS pricing practices and processes.

• The exploratory case study presented in Publication IV was based on static information obtained from 15 SaaS companies through semi-structured interviews. Conducting longitudinal case studies with data sources beyond interviews is essential for evaluating SaaS pricing processes and assessing their efficiency and might lead to a more extensive and comprehensive taxonomy of SaaS pricing aspects, practices, and processes.

• Finally, further research might employ design science and action research to deliver decision-support frameworks, algorithms, and tools. In many cases, effective pricing is impossible without effective economic analysis. Such an analysis can and should be based on existing economic works, but, to be helpful to a wide range of companies, these models must be turned into straightforward and easy-to-use algorithms and decision-support tools.

6 Conclusion

The growth of the SaaS market and SaaS penetration in the IT and business landscapes shows no signs of slowing down. This dissertation, to a large extent, focuses on the exploratory investigation of SaaS pricing. It aimed to explore how software companies price their SaaS solutions and assess how associated practices and processes can be improved. A series of studies employing a mixture of qualitative and quantitative methods was performed to reach the stated aim.

In particular, an MLR of existing publications was conducted to form a clear picture of the current state of SaaS pricing research and practice. The review created a taxonomy of pricing-related concepts, classifying SaaS pricing aspects and the factors and challenges affecting SaaS providers. Next, a survey of pricing employed in existing SaaS companies was conducted. The market overview was based on the detailed analysis of 220 pricing pages of SaaS companies available for analysis. In continuation, a case study of 15 SaaS companies was performed to explore decision processes and practices related to SaaS pricing in software companies.

Along with that, an integrated simulation model of SaaS pricing as an example of a solution that might be used in SaaS pricing decision-making is proposed to illustrate trade-offs between pricing mechanisms and SaaS characteristics. The simulation model estimated the efficiency of using dynamic pricing mechanisms to be made. Although the model allows obtaining a better understanding of the usage of different dynamic pricing mechanisms, it also shows an approach for analyzing a comprehensive pricing strategy as a portfolio of multiple pricing mechanisms. Above all, the observed growth of interest in the SaaS model in the industry is at odds with the interest of researchers in the business aspects of SaaS, at least when it comes to pricing.

This dissertation also intends to reverse the current situation by exploring what is missing in the current research on SaaS pricing and what research is needed for practitioners. A number of possible paths for further investigation into issues related to SaaS pricing by broadening the scope of the research methods, extending the range of data used for the analysis, and deepening the level of the analysis are outlined in the dissertation.

The dissertation ultimately aims to empower and guide software companies in evolving their SaaS pricing practices. In the long run, this should lead to the greater sustainability of the SaaS industry as superior SaaS solutions will not face market failure due to inappropriate pricing leading to poor customer acquisition, monetization, and retention.

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Publication I

Saltan, A., Nikula, U., Seffah, A., and Yurkov, A.

A Dynamic Pricing Model for Software Products Incorporating Human Experiences

Reprinted with permission from

Lecture Notes in Business Information Processing Vol. 240, 2016

A Dynamic Pricing Model for Software Products Incorporating Human Experiences

Andrey Saltan^1,2(&), Uolevi Nikula¹, Ahmed Seffah¹, and Alexander Yurkov²

1 Department of Software and Innovation,

Lappeenranta University of Technology, Skinnarilankatu 34, 53851 Lappeenranta, Finland

{uolevi.nikula,ahmed.seffah}@lut.fi

2 Department of Information Systems in Economics, St. Petersburg State University, 7/9 Universitetskaya nab.,

199034 St. Petersburg, Russia {a.saltan,a.yurkov}@spbu.ru

Abstract. At the age of software as a service (SasS) and cloud computing as compared to what is used to be earlier, designing product strategies is a chal-lenging concern for software product management researchers. Comparative statics models are considered to identify software market characteristics while assessing the managerial decisions during the software product strategy design.

However, their applicability in dynamic market analysis is rather limited.

Important concerns in dynamic market such as dynamic pricing cannot be fully estimated. This motivated the development of a simulation-based dynamic model to evaluate the efﬁciency and effectiveness of using different pricing models. The proposed (simulation) approach given in details in this paper can be used in conducting complex analysis of software product strategy that involves consideration of product strategy as a portfolio of interrelated solutions rather than a set of independent managerial decisions.

Keywords: Software product strategySoftware marketDecision making

Pricing modelSimulation model

1 Introduction

The ever changing software markets make it difﬁcult for software development com-panies, big and small ones, to improve and package their products as well as to customize it to the diverse markets and consumer needs. They also have to look for other discontinuous innovation or disruptive technology that will revolutionize their industry or require heavy reengineering and re-packing of their software products.

Furthermore, the rapid change that characterizes software industry today results in high instability and uncertainty, which may make product strategy development meaning-less. In reality, the inverse proves to be true, and in this case product strategy becomes even more crucial than in other industries due to the nature of high-tech markets [5].

Two decades ago, the software companies’product strategies were slightly different from the strategies of any other goods. Software products were sold as physical

A. Maglyas and A.-L. Lamprecht (Eds.): ICSOB 2016, LNBIP 240, pp. 135–144, 2016.

DOI: 10.1007/978-3-319-40515-5_10

products on a CD or a floppy disc. Most often, they are packaged in two or three versions (e.g. professional/domestic, beginner/advanced, etc.). Nowadays, software as a service, mobile, web-service and the future services for the Internet of things are making software very different from other goods. We see them as indestructibility, transmutability, and reproducibility [9]. The evolution of the Internet has challenged the company to reconstruct their product strategy.

From scientiﬁc point of view, product strategy lies in the intersection of product design and development, marketing and sales, strategy and business. There is no universal product strategy, neither a unifying theory is. Each company has its own strategy that takes into account the software product speciﬁcations, the market segment characteristics as well as the consumers’experiences, needs and expectations. Various models have tried to address these notions concerning product strategy.

The traditional comparative statics models were introducedﬁrst to identify software market characteristics and qualitatively assess factors determining its development.

Software market and software product characteristics being identiﬁed offer unprece-dented opportunities to companies. However, the application scope of these models as a tool for qualitative and dynamic market analysis are very limited. The development of simulation-based models to design a product strategy based on the dynamic presen-tation of software users’experiences seems to be potentially an efﬁcient approach. The mentioned task has both theoretical and practical effect on development of informa-tional economy since business models and product strategies of todays market par-ticipants –the software companies–up to now are being developed intuitively, and later being corrected according to cut-and-try method. With this economic viability and effectiveness of business models can be tested by their approbation at the real market, while companies have no instruments for their justiﬁcation in advance.

In this paper, we investigate one speciﬁc model for evaluating the potential of the dynamic pricing strategy. The main objective of this paper is not only to develop a practical model that industry can use. This is a long-term objective that requires years of research. More precisely the key objective is to develop a ground for studying market analysis at the research level. Still, possibility of carrying out complex analysis of software product strategy based on the proposed model is discussed.

2 Background and Works Related

Our research is based on the previous investigations on software economics in general and pricing aspects of product strategy in particular. Studying the existing academic papers and analytical research reveals the following software market determinants describing the fundamental characteristics of software as digital goods:

1. The software markets are determined by network effect. Direct network effect or the so-called Demand Side Economies of Scale results in the fact that potential con-sumers’value and willingness to buy software correlates with total amount of users existing. Indirect network effect or the so-called Supply Side Economies of Scale create the situation in which the increase in sales of the original software results in rising sales of complementary goods, which in turn increases the value of the original product for users [10,14].

136 A. Saltan et al.

2. Economies of scale and network effect cause non-stop price pressure for the companies operating on software markets and make for the establishment of monopolies and oligopolies on these markets [13].

3. In addition to the network effect, the important property of software being a digital good is the possibility of being copied easily without signiﬁcant loss in quality. This results in unauthorized use or piracy. The practice shows that piracy being on high level on a speciﬁc regional market prevents companies from reducing it by their own. This makes companies design their product strategy taking piracy as one of market characteristics and trying to minimize their ﬁnancial losses or even improving their non-ﬁnancial indicators [3,4,12].

4. Extremely low costs of reproducing software results in the situation in which companies have a structure of expenses with high ﬁxed expenses for software development and incomparably small variable expenses [1].

Under the name of a software company, we mean companies dealing with R&D, distribution and maintenance of general software products aimed at the wide range of consumers. Software consumers are natural persons who buy produced software products for their own purposes.

The above mentioned software products and software markets characteristics result in an extremely diverse list of options available for designing software product strategy.

While offering value to the consumers at the right price is the prime aim of software companies, versioning and pricing plays a key role in most software companies’ product strategies [10]. Monopolistic competition market and costs structure let soft-ware companies to establish any pricing policy they need. Its inadequacy, though, will soon result in seriousﬁnancial problems.

Recently, several studies [6,8,9] have examined the structure of the pricing policy.

Despite different approaches all the above mentioned studies identiﬁed dynamic pricing as one of the key options in designing the pricing strategy supported by price bundling and price discrimination. As far as we know, the problem of choosing the optimal dynamic pricing model has not been tackled in the literature, especially with the uncertainty in consumer valuation, network effect, and piracy. We believe it to be the result of lack of opportunity to carry out such analysis by means of microeconomic

In document Revealing the State of Software-as-a-Service Pricing (sivua 46-121)